CAMTRAPPER– CAMera TRap Archive and Public Portal for Exploration & Research

• Applicants: Dr. Martin Jansen; Dr. Claus Weiland
• Subject Area: Ecology and Biodiversity of Animals and Ecosystems, Organismic Interactions
• Term: since 2021
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 437771903

The growing human impact on nature and the environment is also increasing the global biodiversity crisis. Constant biomonitoring at selected locations is therefore more important than ever to control populations, identify human-nature conflicts and find solutions. Today there are for example camera traps and other new techniques and possibilities of autonomous observation of nature, data acquisition, and storage. On the one hand, however, there is a lack of research data infrastructure for the large amounts of data that are permanently generated from biomonitoring or camera trap projects. Only an archiving and cataloging ensures a sustainable backup and accessibility to the data in the future. On the other hand, in the field of nature conservation (for example, national park monitoring or monitoring of protected or invasive species), rapid data analysis is of fundamental importance in order to respond to changes accordingly. There are new and promising approaches for time and resource saving analyses through the use of deep learning and related methods of artificial intelligence. On the part of science and nature conservation, there is a great need for both archiving and rapid analysis of this "big data". The combination of archive and analysis on just one platform, as proposed herein for the first time, therefore has great potential.The planned project aims to develop an online platform for camera case data that combines several functions:(1) CAMTRAPPER is intended to be a long-term and sustainable archive of camera-case data that should allow other scientific users to publish their data and preserve it for future generations. The connection to a scientific collection structure (the Senckenberg collections) is a central concern of the portal. (2) Furthermore, deep learning algorithms are to be implemented in the portal, so that the autonomous classification of camera trap images by means of artificial intelligence will also be possible as a service. (3) Based on own case studies, a "self-analyzing" monitoring infrastructure ("Dynamic Biomonitoring") should be developed and established. (4) The platform itself will also be opened to citizen scientists within Citizen Science projects. (5) Communicating the importance of the archive as well as results gained is a central concern of the project.

• DFG Programme: Research data and software (Scientific Library Services and Information Systems)
• Co-Investigators: Dr. Eike Lena Neuschulz; Dr. Marco Schmidt